Smart integration of water, energy, agriculture, and environmental systems can create synergies, increase socio-economic benefits, and minimize environmental impact. However, effective planning of integrated water-energy-food-environment systems (iWEFEs) requires high resolution temporal and spatial data on various environmental and socioeconomic variables. Insufficient data availability and accessibility hampers the implementation of iWEFEs, particularly in remote areas of low- and middle-income countries. Addressing this gap, first, essential variables for the planning of iWEFEs are identified. Next, remote datasets are evaluated and selected regarding their suitability to serve for the planning of iWEFEs using a multi-criteria-analysis considering data accessibility, spatial coverage, spatial resolution, temporal resolution, and temporal coverage. Remote and in-situ data collection for the identified WEFE variables are implemented using a pilot case study of a smallholder farm in the data-scarce tropics of Costa Rica. The remote data collection is automated via APIs to open servers, data analysis and data visualization scripts, and complemented by an online survey. In-situ measurements are recommended to address data gaps in remote sensing, which are especially prevalent in the water domain. The research shall lay the foundation for free, open and automated data collection enabling the planning of iWEFEs worldwide.